Unmanned aerial vehicle (UAV) photogrammetry is an emerging means of acquiring high-precision rapid spatial information and data because it is cost-effective and highly efficient. However, securing uniform quality in the results of UAV photogrammetry is difficult due to the use of low-cost navigation devices, non-surveying cameras, and rapid changes in shooting locations depending on the aircraft’s behavior. In addition, no specific procedures or guidelines exist for performing quantitative quality tests or certification methods on UAV images. Additionally, test tools for UAV image quality assessment only use the ground sample distance (GSD), often resulting in a reduced image quality compared with that of manned aircraft images. In this study, we performed a modulation transfer function (MTF) analysis using a slanted edge target and a GSD analysis to confirm the necessity of MTF analysis in UAV image quality assessments. In this study, we aimed to address this issue by conducting a modulation transfer function (MTF) analysis using a slanted edge target and a ground sample distance (GSD) analysis. This was carried out to confirm the necessity of MTF analysis in evaluating UAV image quality. Furthermore, we analyzed the impact of flight height and mounted sensors on image quality at different study sites.

Average global temperatures have risen by approximately 1.1 °C above pre-industrial levels, prompting South Korea and many other countries to set a carbon neutrality goal by 2050. Expanding green spaces has been proposed as a landscape-based approach to achieving urban carbon neutrality. However, the dense development of urban areas presents spatial and economic constraints in securing new green spaces. As a result, street trees, an existing urban green infrastructure, are increasingly regarded as a practical solution to enhancing carbon storage. Nevertheless, concerns have been raised that street trees planted without a systematic management plan may suffer from reduced vitality, leading to diminished carbon storage capacity. Ultimately, these conditions can result in increased tree mortality, turning what should be carbon sinks into sources of emissions. Such tree mortality not only results in the loss of carbon storage but also degrades the urban landscape, making systematic street tree management essential. This study aimed to address these challenges by developing an effective diagnostic approach to assess street tree growth conditions and identify methods to improve their carbon storage capacity. The methodology included identifying diagnostic indicators through a review of prior research and conducting field surveys on 72 Ginkgo biloba in Dalseo-gu, Daegu Metropolitan City. Correlation and regression analyses were performed, taking into account both growth diagnostic indicators and environmental variables. The results revealed that traffic volume and service population were the main environmental factors affecting the carbon storage capacity of Ginkgo biloba. Among the individual growth characteristics, tree height (β = 0.514), chlorophyll content (β = 0.26), and stem vigor (β = 0.216) were found to have significant influences. Based on these findings, this study proposed a management strategy to enhance the growth and carbon storage potential of urban street trees. These results are expected to serve as a vital foundational resource, contributing to the development of practical street tree management guidelines that support sustainable urban environments and climate change mitigation efforts.

For sustainable, national landscape-planning, this study focused on land cover changes, landscape analysis methods from various perspectives on the landscape, legal system analysis related to landscape planning, and analysis of a basic spatial map for landscape planning. First of all, in Korea the focus is on the aesthetic aspect of the landscape, while foreign countries look at the landscape from multiple perspectives and tried to solve the problem of landscape damage on this basis. Next, looking at the changes in land cover, it was found that the urbanized area increased significantly, but the area of agricultural land and wetlands decreased significantly due to development plans. In addition, looking at the contents of the landscape plan in terms of the legal system, the legal system of the Republic of Korea included a multifunctional aspect of the landscape, but the contents were only at the level of policy suggestions. Finally, through a review of a basic spatial map for landscape planning, it was found that among various basic spatial maps, the biotope map is highly likely to be used when establishing national landscape plans. The results of this study are meaningful in that they have not only established the concept of landscape in terms of multifunctionality but also established improvement measures in terms of legal and institutional aspects and the basic spatial map.

This study aims to establish an integrated landscape planning model and explore its applicability through the convergence of digital twin technology. The primary goal is to address the fragmented implementation of landscape policies and to provide a systematic framework that enhances efficiency and visualization in the planning process. To this end, text-mining analysis was conducted to extract relevant laws, statutory plans, and project data, thereby identifying key factors for model construction. The resulting model integrates conservation-oriented and recreation-oriented modules, presenting a practical approach for landscape management. Furthermore, by utilizing Blender 3D and OpenStreetMap, this study demonstrates the process through which a digital twin visualizes and simulates the spatial characteristics of the actual target site, thereby validating its utility in decision-making and stakeholder communication. The results indicate that the landscape planning model was reconfigured and integrated into 6 detailed implementation measures and 41 specific indicators. Moreover, the model visually linked 36 laws and approximately 70 plans and projects. Ultimately, the study confirms that the proposed approach provides a dynamic, data-driven platform for sustainable landscape management.